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An Efficient and Novel Approach for Predicting Kohn-Sham Total Energy: Bootstrapping a Cooperative Model Framework with Minimal Viable Theoretical Data

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State of Charge and Temperature-Dependent Impedance Spectra Regeneration of Lithium-ion Battery by Duplex Learning Modeling

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Data on Machine Learning regenerated Lithium-ion battery impedance

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ccImpute: an accurate and scalable consensus clustering based algorithm to impute dropout events in the single-cell RNA-seq data

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Regeneration of Lithium-ion Battery Impedance using a Novel Machine Learning Framework and Minimal Empirical Data

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DCEM: An R package for clustering big data via data-centric modification of Expectation Maximization

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Building Machine Learning Systems for Multi-Atoms Structures: CH3NH3PbI3 Perovskite Nanoparticles

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Atom Classification with Machine Learning and Correlations among Physical Properties of ZnO Nanoparticle

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Rare-class Learning over Mg-Doped ZnO Nanoparticles

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Effect of Mg content on electronic structure, optical and structural properties of amorphous ZnO nanoparticles: A DFTB study

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